class_docstr: Abstract register class.
  
  The register class indicates how to load a dataset from the name. Abstract
  methods `register.xyz()` have the same API as `tfds.xyz()`.
  
  ```
  register = MyRegister()
  register.list_builders()
  builder = register.builder('kaggle', 'my_dataset')
  ```
  
  Subclasses indicates how dataset code are fetched:
  
  * DataDirRegister: Find the dataset by looking at pre-generated dataset
    inside `data_dir`.
  * RemoteRegister: Find the dataset by fetching remote generation script.
docstr: Returns the `tfds.core.DatasetBuilder` instance.
  
  Contrary to `tfds.builder`, `builder_name` here is already normalized (
  `my_dataset/my_config` -> `my_dataset`, `{'config': 'my_config'}`).
  
  Args:
    name: Builder name (e.g. `DatasetName('kaggle:mnist')`)
    **builder_kwargs: Additional kwargs forwarded to
      `tfds.core.DatasetBuilder` (version, config,...)
  
  Returns:
    builder
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code: def builder(
      self,
      name: naming.DatasetName,
      **builder_kwargs: Any,
  ) -> dataset_builder.DatasetBuilder:
      """Returns the `tfds.core.DatasetBuilder` instance.
  
      Contrary to `tfds.builder`, `builder_name` here is already normalized (
      `my_dataset/my_config` -> `my_dataset`, `{'config': 'my_config'}`).
  
      Args:
        name: Builder name (e.g. `DatasetName('kaggle:mnist')`)
        **builder_kwargs: Additional kwargs forwarded to
          `tfds.core.DatasetBuilder` (version, config,...)
  
      Returns:
        builder
      """
      raise NotImplementedError
  
file_path: datasets/tensorflow_datasets/core/community/register_base.py
imports: import abc
  from typing import Any, Iterable, List, Type
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import naming
label_desc: Use image node_id 4 for calling the BaseRegister obj's underlying member method code with example usage: obj.builder(name) without return types